Expanding the integration interval with a pre-defined schedule turns out to be useful for PINNs as well. In [1]}, the authors propose to split the full interval on smaller sub-intervals and solve equations on each individual interval in turn such that the solution at the border of the previous sub-interval is used as the initial condition for the next sub-interval. This algorithm needs a pre-defined discretization scheme, which makes it similar to the classical numerical solvers. However, this approach has several limitations: 1) training requires a hand-crafted discretization scheme, 2) the solution is modeled by several neural networks trained on individual sub-intervals.
